Resting state fMRI functional connectivity-based classification using a convolutional neural network architecture RJ Meszlényi, K Buza, Z Vidnyánszky Frontiers in neuroinformatics 11, 61, 2017 | 154 | 2017 |
A specialized histone H1 variant is required for adaptive responses to complex abiotic stress and related DNA methylation in Arabidopsis K Rutowicz, M Puzio, J Halibart-Puzio, M Lirski, M Kotliński, MA Kroteń, ... Plant Physiology 169 (3), 2080-2101, 2015 | 133 | 2015 |
Feedback prediction for blogs K Buza Data analysis, machine learning and knowledge discovery, 145-152, 2013 | 133 | 2013 |
Resting state fMRI functional connectivity analysis using dynamic time warping RJ Meszlényi, P Hermann, K Buza, V Gál, Z Vidnyánszky Frontiers in neuroscience 11, 75, 2017 | 98 | 2017 |
Drug-target interaction prediction: a Bayesian ranking approach L Peska, K Buza, J Koller Computer methods and programs in biomedicine 152, 15-21, 2017 | 83 | 2017 |
Insight: efficient and effective instance selection for time-series classification K Buza, A Nanopoulos, L Schmidt-Thieme Advances in Knowledge Discovery and Data Mining: 15th Pacific-Asia …, 2011 | 80 | 2011 |
Success: a new approach for semi-supervised classification of time-series K Marussy, K Buza Artificial Intelligence and Soft Computing: 12th International Conference …, 2013 | 64 | 2013 |
Motif-based classification of time series with bayesian networks and svms K Buza, L Schmidt-Thieme Advances in Data Analysis, Data Handling and Business Intelligence …, 2010 | 58 | 2010 |
Nearest neighbor regression in the presence of bad hubs K Buza, A Nanopoulos, G Nagy Knowledge-Based Systems 86, 250-260, 2015 | 55 | 2015 |
Drug–target interaction prediction with bipartite local models and hubness-aware regression K Buza, L Peška Neurocomputing 260, 284-293, 2017 | 52 | 2017 |
Hubness-aware classification, instance selection and feature construction: Survey and extensions to time-series N Tomašev, K Buza, K Marussy, PB Kis Feature selection for data and pattern recognition, 231-262, 2015 | 50 | 2015 |
It ticket classification: The simpler, the better A Revina, K Buza, VG Meister IEEE Access 8, 193380-193395, 2020 | 49 | 2020 |
Hubness-aware kNN classification of high-dimensional data in presence of label noise N Tomašev, K Buza Neurocomputing 160, 157-172, 2015 | 44 | 2015 |
Scalable event-based clustering of social media via record linkage techniques T Reuter, P Cimiano, L Drumond, K Buza, L Schmidt-Thieme Proceedings of the international AAAI conference on web and social media 5 …, 2011 | 42 | 2011 |
Folksonomy-based collabulary learning L Balby Marinho, K Buza, L Schmidt-Thieme The Semantic Web-ISWC 2008: 7th International Semantic Web Conference, ISWC …, 2008 | 36 | 2008 |
Storage-optimizing clustering algorithms for high-dimensional tick data K Buza, GI Nagy, A Nanopoulos Expert Systems with Applications 41 (9), 4148-4157, 2014 | 35 | 2014 |
Fusion methods for time-series classification KA Buza Peter Lang Verlag, 2011 | 35 | 2011 |
Time series classification and its applications K Buza Proceedings of the 8th International Conference on Web Intelligence, Mining …, 2018 | 31 | 2018 |
Time-series classification based on individualised error prediction K Buza, A Nanopoulos, L Schmidt-Thieme 2010 13th IEEE International Conference on Computational Science and …, 2010 | 27 | 2010 |
Feature selection with a genetic algorithm for classification of brain imaging data A Szenkovits, R Meszlényi, K Buza, N Gaskó, RI Lung, M Suciu Advances in feature selection for data and pattern recognition, 185-202, 2018 | 26 | 2018 |